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Record W4399425484 · doi:10.1038/s41380-024-02601-w

Epigenetic alterations in patients with anorexia nervosa—a systematic review

2024· review· en· W4399425484 on OpenAlexaff
Larissa Käver, Anke Hinney, Luisa Sophie Rajcsanyi, Hannah Benedictine Maier, Helge Frieling, Howard Steiger, Clara Voelz, Cordian Beyer, Stefanie Trinh, Jochen Seitz

Bibliographic record

VenueMolecular Psychiatry · 2024
Typereview
Languageen
FieldMedicine
TopicChild Nutrition and Feeding Issues
Canadian institutionsMcGill University
Fundersnot available
KeywordsEpigeneticsDNA methylationDiseaseEpigenomeBiomarkerAnorexia nervosaBioinformaticsMedicineBiologyGeneticsPsychiatryGeneInternal medicineEating disordersGene expression

Abstract

fetched live from OpenAlex

Anorexia nervosa (AN) is a complex metabolic and psychological disorder that is influenced by both heritable genetic components and environmental factors. Exposure to various environmental influences can lead to epigenetically induced changes in gene expression. Epigenetic research in AN is still in its infancy, and studies to date are limited in determining clear, valid links to disease onset and progression are limited. Therefore, the aim of this systematic review was to compile and critically evaluate the available results of epigenetic studies specifically in AN and to provide recommendations for future studies. In accordance with the PRISMA guidelines, a systematic literature search was performed in three different databases (PubMed, Embase, and Web of Science) through May 2023. Twenty-three original papers or conference abstracts on epigenetic studies in AN were collected. Epigenome-wide association studies (EWASs), which analyze DNA methylation across the genome in patients with AN and identify potential disease-relevant changes in promoter/regulatory regions of genes, are the most promising for future research. To date, five EWASs on AN have been published, suggesting a potential reversibility of malnutrition-induced epigenetic changes once patients recover. Hence, determining differential DNA methylation levels could serve as a biomarker for disease status or early diagnosis and might be involved in disease progression or chronification. For future research, EWASs with a larger sample size, longitudinal study design and uniform methods should be performed to contribute to the understanding of the pathophysiology of AN, the development of individual interventions and a better prognosis for affected patients.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.070
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.307
Teacher spread0.295 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations23
Published2024
Admission routes1
Has abstractyes

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